Assessing Effects on Long-term Survival after Early Termination of Randomized Trials

In this paper we present an approach to using historical control data to augment information from a randomized controlled clinical trial, when it is not possible to continue the control regimen to obtain the most reliable and valid assessment of long term treatment effects. Using an adjustment procedure to the historical control data, we investigate a method of estimating the long term survival function for the clinical trial control group and for evaluating the long term treatment effect. The suggested method is simple to interpret, and particularly motivated in clinical trial settings when ethical considerations preclude the long term follow-up of placebo controls. A simulation study reveals that the bias in parameter estimates that arises in the setting of group sequential monitoring will be attenuated when long term historical control information is used in the proposed manner. Data from the first and second National Wilms' Tumor studies are used to illustrate the method.     

An efficient sequential design of clinical trials

We propose an efficient group sequential monitoring rule for clinical trials. At each interim analysis both efficacy and futility are evaluated through a specified loss structure together with the predicted power. The proposed design is robust to a wide range of priors, and achieves the specified power with a saving of sample size compared to existing adaptive designs. A method is also proposed to obtain a reduced-bias estimator of treatment difference for the proposed design. The new approaches hold great potential for efficiently selecting a more effective treatment in comparative trials. Operating characteristics are evaluated and compared with other group sequential designs in empirical studies. An example is provided to illustrate the application of the method.     

Estimation of the association for bivariate doubly censored data

We study the problem of estimating the association between two related survival variables when they follow a copula model and the bivariate doubly censored data is available. A two-stage estimation procedure is proposed and the asymptotic properties of the proposed estimator are established. Simulation studies are conducted to investigate the finite sample properties of the proposed estimate.     

An Inverse-Probability-Weighted Approach to the Estimation of Successive Duration Times under Left-Truncation and Right-Censoring

In incident cohort studies, survival data often include subjects who have had an initiate event at recruitment and may potentially experience two successive events (first and second) during the follow-up period. Since the second duration process becomes observable only if the first event has occurred, left-truncation and dependent censoring arise if the two duration times are correlated. To confront the two potential sampling biases, Chang and Tzeng (2006 Chang , S.-H. , Tzeng , S.-J. (2006). Noparametric estimation of sojourn time distributions for truncated serial event data- a weight-adjusted approach. Lifetime Data Anal. 53–67.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) provided an inverse-probability-weighted (IPW) approach for estimating the joint probability function of successive duration times. In this note, an alternative IPW approach is proposed. A simulation study is conducted to compare the two IPW approaches.     

Construction of Confidence Intervals for the IVIean of a Population Containing Many Zero Values

The likelihood ratio method is used to construct a confidence interval for a population mean when sampling from a population with certain characteristics found in many applications, such as auditing. Specifically, a sample taken from this type of population usually consists of a very large number of zero values, plus a small number of nonzero values that follow some continuous distribution. In this situation, the traditional confidence interval constructed for the population mean is known to be unreliable. This article derives confidence intervals based on the likelihood-ratio-test approach by assuming (1) a normal distribution (normal algorithm) and (2) an exponential distribution (exponential algorithm). Because the error population distribution is usually unknown, it is important to study the robustness of the proposed procedures. We perform an extensive simulation study to compare the percentage of confidence intervals containing the true population mean using the two proposed algorithms with the percentage obtained from the traditional method based on the central limit theorem. It is shown that the normal algorithm is the most robust procedure against many different distributional error assumptions.     

天然气产量季节预测模型的比较与选择

随着气田企业规模的扩大和竞争的加剧,需要建立一套完整的短期天然气产量预测方法及模型,以预测未来的产量发展趋势,故提出三种基于时间序列预测模型:布朗指数平滑法(Smooth)、季节系数法时间序列的预测、用于时间序列的灰色系统预测方法.但是普通时间序列预测模型的参数难以估计并且模型较难预测具有季节特征的时间序列问题,根据天然气产量的季节性、周期性特点,实验结果表明:季节系数法时间序列的预测能够对带有季节特征的历史数据进行有效预测,对进行气田企业的安全生产都具有一定的理论和实践价值.     

关于高校学生思想政治工作的思考

从当前高校思想政治工作面临的新问题出发 ,对加强和改进高校思想政治工作进行了分析和思考 ,提出了新形势下对这一工作正确定位及开展好这项工作的对策。     

文学批评理论的双重话语--基于问题意识的再审

作为文学研究的当代知识范型,批评理论在对传统文论的超越中,逐步形成了自己阐释文学的基本思路。新时期以来的中国文论形态却往往从审美关系论域出发,以批评模式对它进行诠释和界说。由此,忽视了贯穿于其中的问题意识与文学研究理论构成之间的对应关联,淡化乃至消解了批评理论的双重性质。正视并阐明当代文学批评理论的话语构成和理论视域,对于当代中国文论更新观念形貌、介入本土文学具有重要的意义。     

由表及里:地方服务型政府建构向度研究

服务型政府效能化与人本化建构是公共管理发展的基本向度,也是我国政府体制改革的目标.多年来,我国地方政府体制改革林林总总,风生水起.但是,由于受转型背景的复杂性、体制体系的惯性以及传统社会结构的粘性等因素制约,总体仍处于表象层面.为此,需要相应支点结构性的循序移位,由表及里,实现地方政府体制改革的路径创新,从而把技术性、手段性改革转变为真正为人民服务的体制性改革.     

大陆与台湾刑法中保安处分制度比较研究

我国 1997年新刑法的颁布 ,标志着我国的刑事实体法又上了一个新的台阶。保安处分制度是现代西方刑法理论和刑法制度的重要组成部分。在刑法修改以前 ,是否应该将该制度引入我国的刑事立法体系 ,引起了我国学者的广泛讨论。本文通过对台湾刑法中的保安处分制度和大陆法律中类似于保安处分制度的保安性措施进行比较分析 ,旨在论证将保安处分制度引入我国大陆刑法的可行性